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Attribute reduction algorithm based on new conditional information quantity

被引：0
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作者：
Inst. of Computer Science and Engineering, Jiangsu Teachers Univ. of Technology, Changzhou 213001, China [1 ]
不详 [2 ]
不详 [3 ]
机构：
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2007年 / 29卷 / 12期
关键词：
Data mining - Decision tables - Heuristic algorithms;
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中图分类号：
学科分类号：
摘要：
To obtain satisfactory relative attribute reduction in decision systems, the relationship between attribute reduction and conditional information quantity is discussed. A new conditional information quantity is proposed. Based on this quantity the new significance of an attribute is defined. The heuristic algorithm for attribute reduction is unified for consistent and inconsistent decision tables and an efficient algorithm for computing conditional information quantity is designed. Theoretical analysis and experimental results show that time complexity of this reduction algorithm is less than that of the existing algorithm based on the conditional information quantity, and that the number of attributes is small after the reduction.
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页码：2154 / 2157
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